{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import plotly.express as px\n",
    "import mytools\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.read_excel(R\"data\\ABtest_actions_full.xlsx\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "解释性研究是关于现象或事物之间因果关系的研究。解释性研究是在描述性研究的基础上，进一步探寻“为什么”。解释性研究要在描述性研究的基础上对变量之间的关系进行分析，以确定它们之间是否存在相关，并进而判断它们之间是否存在因果关系。\n",
    "\n",
    "在定量研究方法中，解释性研究通常是首先提出研究假设，然后从理论假设出发，设计出调查方案（收集资料的方案）并采用各种调查方法去收集经验材料，最后通过对资料的分析来验证假设，达到对社会现象进行理论解释的目的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 明确数据分析目标\n",
    "\n",
    "本案例属于解释性研究，也可以认为是评价性研究。\n",
    "\n",
    "某在线教育机构，需要评价网站首页改版是否有效，进行了在线AB测试，在一段时间内，将访问用户随机分成2部分，分别访问原首页和改版后首页，搜集用户的浏览、点击和报名行为。\n",
    "\n",
    "研究假设：改版后报名比例高于改版前的报名比例。\n",
    "原假设：改版后报名比例小于等于改版前的报名比例。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据获取\n",
    "\n",
    "本研究采用在线AB实验法，在XXX与XX期间，对访问网站首页的用户进行随机分组分流，50%的用户访问原首页，50%的用户访问新首页，共获得样本数据XXX个。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据清理\n",
    "\n",
    "## 查看所有空白值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>id</th>\n",
       "      <th>group</th>\n",
       "      <th>action</th>\n",
       "      <th>duration</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2016-09-24 22:43:35.120</td>\n",
       "      <td>701620</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>2016-09-30 11:57:44.059</td>\n",
       "      <td>802405</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>2016-09-30 17:17:07.709</td>\n",
       "      <td>524941</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>2016-10-01 08:40:31.380</td>\n",
       "      <td>381758</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>2016-10-03 20:08:57.011</td>\n",
       "      <td>757165</td>\n",
       "      <td>control</td>\n",
       "      <td>enroll</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>605</th>\n",
       "      <td>2016-10-10 11:26:20.715</td>\n",
       "      <td>678491</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>731</th>\n",
       "      <td>2016-10-14 04:19:46.021</td>\n",
       "      <td>878418</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1145</th>\n",
       "      <td>2016-10-27 04:48:21.083</td>\n",
       "      <td>767153</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1212</th>\n",
       "      <td>2016-10-29 09:37:41.649</td>\n",
       "      <td>196115</td>\n",
       "      <td>control</td>\n",
       "      <td>enroll</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1238</th>\n",
       "      <td>2016-10-29 23:41:44.643</td>\n",
       "      <td>542999</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1311</th>\n",
       "      <td>2016-11-01 05:42:50.439</td>\n",
       "      <td>599303</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1322</th>\n",
       "      <td>2016-11-01 10:07:53.009</td>\n",
       "      <td>281907</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663</th>\n",
       "      <td>2016-11-11 13:56:17.708</td>\n",
       "      <td>742859</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1768</th>\n",
       "      <td>2016-11-14 12:04:15.515</td>\n",
       "      <td>860051</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1966</th>\n",
       "      <td>2016-11-20 09:06:10.553</td>\n",
       "      <td>864971</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2457</th>\n",
       "      <td>2016-12-04 22:55:30.055</td>\n",
       "      <td>443391</td>\n",
       "      <td>control</td>\n",
       "      <td>enroll</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2576</th>\n",
       "      <td>2016-12-08 11:34:10.808</td>\n",
       "      <td>928935</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2700</th>\n",
       "      <td>2016-12-11 18:23:52.131</td>\n",
       "      <td>417569</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2766</th>\n",
       "      <td>2016-12-13 10:17:36.711</td>\n",
       "      <td>496865</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2834</th>\n",
       "      <td>2016-12-14 17:24:26.749</td>\n",
       "      <td>429709</td>\n",
       "      <td>control</td>\n",
       "      <td>enroll</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3660</th>\n",
       "      <td>2017-01-07 08:14:30.071</td>\n",
       "      <td>631083</td>\n",
       "      <td>control</td>\n",
       "      <td>enroll</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3754</th>\n",
       "      <td>2017-01-10 01:45:10.342</td>\n",
       "      <td>403964</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3758</th>\n",
       "      <td>2017-01-10 03:04:52.819</td>\n",
       "      <td>883792</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3798</th>\n",
       "      <td>2017-01-11 05:16:49.001</td>\n",
       "      <td>910942</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3965</th>\n",
       "      <td>2017-01-15 20:17:33.700</td>\n",
       "      <td>508697</td>\n",
       "      <td>control</td>\n",
       "      <td>view</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   timestamp      id    group  action  duration\n",
       "12   2016-09-24 22:43:35.120  701620  control    view       NaN\n",
       "227  2016-09-30 11:57:44.059  802405  control    view       NaN\n",
       "236  2016-09-30 17:17:07.709  524941  control    view       NaN\n",
       "261  2016-10-01 08:40:31.380  381758  control    view       NaN\n",
       "367  2016-10-03 20:08:57.011  757165  control  enroll       NaN\n",
       "605  2016-10-10 11:26:20.715  678491  control    view       NaN\n",
       "731  2016-10-14 04:19:46.021  878418  control    view       NaN\n",
       "1145 2016-10-27 04:48:21.083  767153  control    view       NaN\n",
       "1212 2016-10-29 09:37:41.649  196115  control  enroll       NaN\n",
       "1238 2016-10-29 23:41:44.643  542999  control    view       NaN\n",
       "1311 2016-11-01 05:42:50.439  599303  control    view       NaN\n",
       "1322 2016-11-01 10:07:53.009  281907  control    view       NaN\n",
       "1663 2016-11-11 13:56:17.708  742859  control    view       NaN\n",
       "1768 2016-11-14 12:04:15.515  860051  control    view       NaN\n",
       "1966 2016-11-20 09:06:10.553  864971  control    view       NaN\n",
       "2457 2016-12-04 22:55:30.055  443391  control  enroll       NaN\n",
       "2576 2016-12-08 11:34:10.808  928935  control    view       NaN\n",
       "2700 2016-12-11 18:23:52.131  417569  control    view       NaN\n",
       "2766 2016-12-13 10:17:36.711  496865  control    view       NaN\n",
       "2834 2016-12-14 17:24:26.749  429709  control  enroll       NaN\n",
       "3660 2017-01-07 08:14:30.071  631083  control  enroll       NaN\n",
       "3754 2017-01-10 01:45:10.342  403964  control    view       NaN\n",
       "3758 2017-01-10 03:04:52.819  883792  control    view       NaN\n",
       "3798 2017-01-11 05:16:49.001  910942  control    view       NaN\n",
       "3965 2017-01-15 20:17:33.700  508697  control    view       NaN"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = df1[df1.isnull().T.any()]\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 删除空值\n",
    "df2 = df1.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>action</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>261869</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>226546</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>286353</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>842279</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>711838</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>724590</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1013</th>\n",
       "      <td>314669</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1351</th>\n",
       "      <td>381744</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1765</th>\n",
       "      <td>831767</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1902</th>\n",
       "      <td>655009</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2293</th>\n",
       "      <td>645047</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2704</th>\n",
       "      <td>510055</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2919</th>\n",
       "      <td>661526</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2952</th>\n",
       "      <td>885859</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3559</th>\n",
       "      <td>661528</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3653</th>\n",
       "      <td>191559</td>\n",
       "      <td>experiment</td>\n",
       "      <td>view</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id       group action\n",
       "5     261869  experiment   view\n",
       "6     226546  experiment   view\n",
       "7     286353  experiment   view\n",
       "8     842279  experiment   view\n",
       "142   711838  experiment   view\n",
       "971   724590  experiment   view\n",
       "1013  314669  experiment   view\n",
       "1351  381744  experiment   view\n",
       "1765  831767  experiment   view\n",
       "1902  655009  experiment   view\n",
       "2293  645047  experiment   view\n",
       "2704  510055  experiment   view\n",
       "2919  661526  experiment   view\n",
       "2952  885859  experiment   view\n",
       "3559  661528  experiment   view\n",
       "3653  191559  experiment   view"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 查看重复值\n",
    "df2[df2.duplicated(subset=['id','group','action'],keep='first')][['id','group','action']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 删除重复值\n",
    "df3 = df2.drop_duplicates(subset=['id'],keep='last')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 查看变量类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "                        0\n",
       "timestamp  datetime64[ns]\n",
       "id                  int64\n",
       "group              object\n",
       "action             object\n",
       "duration          float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
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   ],
   "source": [
    "df3.dtypes.to_frame()"
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  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>timestamp</th>\n",
       "      <td>datetime64[ns]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>int64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <td>category</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>action</th>\n",
       "      <td>category</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>duration</th>\n",
       "      <td>float64</td>\n",
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      "text/plain": [
       "                        0\n",
       "timestamp  datetime64[ns]\n",
       "id                  int64\n",
       "group            category\n",
       "action           category\n",
       "duration          float64"
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   "source": [
    "# 指定变量的类型\n",
    "df4 = df3.astype({\n",
    "    'group': 'category',\n",
    "    'action': 'category',\n",
    "})\n",
    "df4.dtypes.to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    4028.000000\n",
       "mean      123.402057\n",
       "std        72.587800\n",
       "min         0.013856\n",
       "25%        67.080495\n",
       "50%       118.487843\n",
       "75%       172.580542\n",
       "max       421.567520\n",
       "Name: duration, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 异常值查找\n",
    "df4['duration'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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          "title": {
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          "xaxis": {
           "automargin": true,
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           "ticks": "",
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           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
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    "fig = px.histogram(df4, x=\"duration\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据清理完毕\n",
    "\n",
    "df = df4.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据分析\n",
    "\n",
    "## 描述统计\n",
    "\n",
    "先描述样本背景，对样本质量进行评价。再描述样本特征信息、样本基本现状，最后描述样本基本态度及其他维度。\n",
    "\n",
    "描述统计分析也应该有理论依据或概念合理的分类。\n",
    "\n",
    "## 推论统计\n",
    "\n",
    "可进行一些相关性、差异性分析以及回归分析。合理分析变量之间的相关性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4028\n"
     ]
    }
   ],
   "source": [
    "## 样本规模\n",
    "N = df.shape[0]\n",
    "print(N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
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       "      <th>百分比</th>\n",
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       "      <th>2</th>\n",
       "      <td>总和</td>\n",
       "      <td>4028</td>\n",
       "      <td>100.00</td>\n",
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      "text/plain": [
       "        group    个数     百分比\n",
       "0  experiment  2079   51.61\n",
       "1     control  1949   48.39\n",
       "2          总和  4028  100.00"
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   "cell_type": "code",
   "execution_count": 15,
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       "      <th>group</th>\n",
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       "  <tbody>\n",
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       "        group  action    频数\n",
       "0     control  enroll   370\n",
       "1     control    view  1579\n",
       "2  experiment  enroll   438\n",
       "3  experiment    view  1641"
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   "source": [
    "# 构建绘图用数据表\n",
    "sun_df = df.groupby([\"group\",'action']).size().reset_index(name='频数')\n",
    "sun_df"
   ]
  },
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       "                     频数      %\n",
       "group      action             \n",
       "control    enroll   370  18.98\n",
       "           view    1579  81.02\n",
       "experiment enroll   438  21.07\n",
       "           view    1641  78.93"
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    "temp = sun_df.set_index(['group','action'])\n",
    "temp['%'] = 100 * (temp / temp.groupby('group').sum())\n",
    "temp.round(2)"
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       "        group  action    频数          %\n",
       "0     control  enroll   370  18.984094\n",
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       "2  experiment  enroll   438  21.067821\n",
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   "source": [
    "fig = px.bar(\n",
    "    sun_df,  # 带绘图数据 \n",
    "    x=\"group\",  # x轴\n",
    "    y=\"%\",  # y轴\n",
    "    color=\"group\",\n",
    "    facet_col=\"action\",  # 列\n",
    ")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
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   ],
   "source": [
    "fig = px.sunburst(sun_df,\n",
    "                  path=['group','action'], \n",
    "                  values='%'\n",
    "                 )\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>group</th>\n",
       "      <th>control</th>\n",
       "      <th>experiment</th>\n",
       "      <th>合计</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>action</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>enroll</th>\n",
       "      <td>18.98</td>\n",
       "      <td>21.07</td>\n",
       "      <td>20.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>view</th>\n",
       "      <td>81.02</td>\n",
       "      <td>78.93</td>\n",
       "      <td>79.94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "group   control  experiment     合计\n",
       "action                            \n",
       "enroll    18.98       21.07  20.06\n",
       "view      81.02       78.93  79.94"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### 双变量统计分析\n",
    "result = pd.crosstab(\n",
    "        df['action'],\n",
    "        df['group'],\n",
    "        normalize='columns',\n",
    "        margins=True,\n",
    "        margins_name='合计',\n",
    "    )*100\n",
    "result.round(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可通过Z检验，对两个比例值是否存在统计显著性差异进行检验。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-1.6503840862221497 0.049432201929688536\n"
     ]
    }
   ],
   "source": [
    "n1 = df.query('group ==\"control\"').shape[0]\n",
    "n2 = df.query('group ==\"experiment\"').shape[0]\n",
    "p1 = df.query('group ==\"control\" and action ==\"enroll\"').shape[0] / n1\n",
    "p2 = df.query('group ==\"experiment\" and action ==\"enroll\"').shape[0] / n2\n",
    "z, p_value = mytools.two_prop_equal_test(n1, n2, p1, p2)\n",
    "print(z, p_value)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过对AB测试的结果进行分析，发现实验组的报名比例较控制组有所增高，p=0.049，具有统计显著性，拒绝原假设，接受研究假设，即：改版后的首页较原版有利于提高学员报名率。"
   ]
  }
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